Finance Toolkit
500+ transparent financial methods calculated from raw statements, not third-party endpoints.
作者提供的说明(英文原文)
Tested, cited economics and finance models and data, with a provenance manifest per result.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"pyeconomics": {
"command": "uvx",
"args": [
"pyeconomics",
"mcp"
]
}
}
}在终端中运行这条命令
claude mcp add pyeconomics -- uvx pyeconomics mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"pyeconomics": {
"command": "uvx",
"args": [
"pyeconomics",
"mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"pyeconomics": {
"type": "stdio",
"command": "uvx",
"args": [
"pyeconomics",
"mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月8日
注册名称已通过 GitHub 账户 pyeconomics-dev 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(1.0.0b1)于11天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。
同一分类中有:Finance Toolkit, SolidInvoice, Korea Tax Calculator
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
500+ transparent financial methods calculated from raw statements, not third-party endpoints.
Create and send invoices and quotes, manage clients, and track payments in SolidInvoice.
Korean tax calculation and tax-audit judgment MCP: 96 tools with statutory citations.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Status: 1.0.0b1 is a beta pre-release on PyPI. Install explicitly with
pip install --pre pyeconomics==1.0.0b1(Python 3.12 or later).
Plain
pip install pyeconomicsstill installs 0.2.6, the stable release.
Pre-releases carry no stability promise until 1.0.0.
pyeconomics provides 50 tested, cited economics and finance model families across 13 domains: foundations, fixed income, derivatives, international, equity, corporate, accounting, portfolio, performance, risk, econometrics, macroeconomics and asset pricing. The data platform adds 31 providers, 171 catalog concepts and live bindings with real-time vintages. Every model is served identically through the Python API, the pyeconomics command line, the REST API (pyeconomics serve), the MCP server (pyeconomics mcp) and tabular or reproducibility-bundle exports. Typed inputs declare units and bounds; every result carries a reproducible provenance manifest. Rates and percentages are decimals: 0.05 means 5%.
Use the 1.0 documentation preview for formulas, assumptions and examples, and the beta release notes for the shipped surfaces and known limitations. See the CLI guide, REST API guide, MCP server guide, exports guide, AI narrative guide, data guide and keys guide to get started. Install optional econometrics, plotting, REST API and MCP support with pip install --pre "pyeconomics[econometrics,plot,server,mcp]==1.0.0b1", or run the MCP server directly with uvx --from "pyeconomics[mcp]==1.0.0b1" pyeconomics mcp.
This beta replaces the 0.2.x API and adds the command line, exports and reproducibility bundles, REST API, MCP server and optional AI narrative on top of the model engine and data platform. The web app arrives in Phase 5; the project roadmap and architecture decisions record that plan. Keep legacy workloads in a separate environment.
0.2.6 is the current stable release of the 0.2.x line: four monetary-policy rules over FRED data.
legacy/0.2.x branch, and its documentation at https://pyeconomics.readthedocs.io/.pyeconomics<1 keep working.This project is not davidrpugh/pyeconomics (computational-economics course code from 2013–14) or pyecon.org (a site teaching Python for economics). The three share only the name.
From 1.0, pyeconomics is licensed under the Apache License 2.0; see also NOTICE. Releases up to and including 0.2.x remain MIT-licensed.
As is; not investment advice. pyeconomics is for educational and informational use only, and is not registered with any regulator.
CFA® and Chartered Financial Analyst® are trademarks owned by CFA Institute. pyeconomics is not affiliated with, endorsed by, or a Prep Provider of CFA Institute.